Although the genome sequence and gene content are available for an increasing number of organisms, eukaryotic selenoproteins remain poorly characterized. In these proteins, selenium (Se) is incorporated in the form of selenocysteine(Sec), the 21st amino acid. Selenocysteine is cotranslationally inserted in response to UGA codons (a stop signal in the canonical genetic code). The alternative decoding is mediated by a stem-loop structure in the 3'UTR of selenoprotein mRNAs (the SECIS element). Selenium is implicated in male infertility, cancer and heart diseases, viral expression and ageing. In addition, most selenoproteins have homologues in which Sec is replaced by cysteine (Cys).Genome biologists rely on the high-quality annotation of genomes to bridge the gap from the sequence to the biology of the organism. However, for selenoproteins, which mediate the biological functions of selenium, the dual role of the UGA codon confounds both the automatic annotation pipelines and the human curators. In consequence, selenoproteins are misannotated in the majority of genome projects. Furthermore, the finding of novel selenoprotein families remains a difficult task in the newly released genome sequences.In the last few years, we have contributed to the exhaustive description of the eukaryotic selenoproteome (set of eukaryotic selenoproteins) through the development of a number of ad hoc computational tools. Our approach is based on the capacity of predicting SECIS elements, standard genes and genes with a UGA codon in-frame in one or multiple genomes. Indeed, the comparative analysis plays an essential role because 1) SECIS sequences are conserved between close species (eg. human-mouse); and 2) sequence conservation across a UGA codon between genomes at further phylogenetic distance strongly suggests a coding function (eg. human-fugu). Our analysis of the fly, human and Takifugu and Tetraodon genomes have resulted in 9 novel selenoprotein families. Therefore, 20 distinct selenoprotein families have been described in eukaryotes to date. Most of these families are widely (but not uniformly) distributed across eukaryotes, either as true selenoproteins or Cys-homologues.The correct annotation of selenoproteins is thus providing insight into the evolution of the usage of Sec. Our data indicate a discrete evolutionary distribution of selenoprotein in eukaryotes and suggest that, contrary to the prevalent thinking of an increase in the number of selenoproteins from less to more complex genomes, Sec-containing proteins scatter all along the complexity scale. We believe that the particular distribution of each family is mediated by an ongoing process of Sec/Cys interconversion, in which contingent events could play a role as important as functional constraints. The characterization of eukaryotic selenoproteins illustrates some of the most important challenges involved in the completion of the gene annotation of genomes. Notably among them, the increasing number of exceptions to our standard theory of the eukaryotic gene and the necessity of sequencing genomes at different evolutionary distances towards such a complete annotation.

Hemp seed proteins (HSP) were investigated for physicochemical and functional properties in model food systems. In addition, the HSP were enzymatically digested and the released peptides investigated as potential therapeutic agents. Membrane isolated HSP (mHPC) were the most soluble with >60% solubility at pH 3-9 when compared to a maximum of 27% for isoelectric pH-precipitated proteins (iHPI). However, iHPI formed emulsions with smaller oil droplet sizes (<1 µm) while mHPI formed bigger oil droplets. The iHPI was subjected to enzymatic hydrolysis using different concentrations (1-4%) of six proteases (pepsin, pancreatin, flavourzyme, thermoase, papain and alcalase) to produce various HSP hydrolysates (HPHs). HPHs had strong in vitro inhibitions of angiotensin converting enzyme (ACE) and renin activities, the two main enzyme systems involved in hypertension. Oral administration of the HPHs to spontaneously hypertensive rats led to fast and persistent reductions in systolic blood pressure. The HPHs also inhibited in vitro activities of acetylcholinesterase (AChE), a serine hydrolase whose excessive activities lead to inadequate level of the cholinergic neurotransmitter, acetylcholine (ACh). Inadequate ACh level in the brain has been linked to neurodegenerative diseases such as dementia and Alzheimer’s disease (AD); therefore, AChE inhibition is a therapeutic target. The 1% pepsin HPH was the most active with up to 54% AChE inhibition at 10 µg/mL peptide concentration. The 1% pepsin HPH (dominated by <1 kDa) was subjected to reverse-phase HPLC peptide purification coupled with tandem mass spectrometry, which led to identification of several peptide sequences. Some of the peptides inhibited activities of both animal and human AChE forms with LYV being the most potent against human AChE (IC50 = 7 µg/ml). Thus the LYV peptide may serve as a useful template for the development of future potent AChE-inhibitory peptidomimetics. In conclusion, several novel AChE-inhibitory peptides were discovered and their amino acid sequences elucidated for the first time. Results from this work identified HSP products that could serve as functional ingredients in the food industry. The work also produced and confirmed the in vitro AChE-inhibitory activities of several new peptide sequences that may serve as therapeutic agents for AD management. / October 2015

Dissertation (Ph.D.)--University of South Florida, 2007. / Title from PDF of title page. Document formatted into pages; contains 197 pages. Includes vita. Includes bibliographical references.

Diss. (sammanfattning) Linköping : Linköpings universitet, 2005. / Härtill 4 uppsatser.

Dissertation (Ph.D.)--University of South Florida, 2007. / Includes vita. Includes bibliographical references (leaves 188-197). Also available online.

Enzymes and biochemical mechanisms essential to survival are under extreme selective pressure and are highly conserved through evolutionary time. We applied this evolutionary concept to barnacle cement polymerization, a process critical to barnacle fitness that involves aggregation and cross-linking of proteins. The biochemical mechanisms of cement polymerization remain largely unknown. We hypothesized that this process is biochemically similar to blood clotting, a critical physiological response that is also based on aggregation and cross-linking of proteins. Like key elements of vertebrate and invertebrate blood clotting, barnacle cement polymerization was shown to involve proteolytic activation of enzymes and structural precursors, transglutaminase cross-linking and assembly of fibrous proteins. Proteolytic activation of structural proteins maximizes the potential for bonding interactions with other proteins and with the surface. Transglutaminase cross-linking reinforces cement integrity. Remarkably, epitopes and sequences homologous to bovine trypsin and human transglutaminase were identified in barnacle cement with tandem mass spectrometry and/or western blotting. Akin to blood clotting, the peptides generated during proteolytic activation functioned as signal molecules, linking a molecular level event (protein aggregation) to a behavioral response (barnacle larval settlement). Our results draw attention to a highly conserved protein polymerization mechanism and shed light on a long-standing biochemical puzzle. We suggest that barnacle cement polymerization is a specialized form of wound healing. The polymerization mechanism common between barnacle cement and blood may be a theme for many marine animal glues. / Dissertation

Among all existing alignment-free methods for comparing biological sequences, the sequence graphical representation provides a simple approach to view, sort, and compare gene structures. The aim of graphical representation is to display DNA or protein sequences graphically so that we can easily find out visually how similar or how different they are. Of course, only the visual comparison of sequences is not enough for the follow-up research work. We need more accurate comparison. This leads us to develop the application of the graphical representation for biological sequences. / In this thesis, we have two main contributions: (1) We construct a protein map with the help of our proposed new graphical representation for protein sequences. Each protein sequence can be represented as a point in this map, and cluster analysis of proteins can be performed for comparison between the points. This protein map can be used to mathematically specify the similarity of two proteins and predict properties of an unknown protein based on its amino acid sequence. (2) We construct a novel genome space with biological geometry, which is a subspace in RN . In this space each point corresponds to a genome. The natural distance between two points in the genome space reflects the biological distance between these two genomes. Our genome space will provide a new powerful tool for analyzing the classification of genomes and their phylogenetic relationships. / Yu, Chenglong. / Adviser: Luk Hing Sun. / Source: Dissertation Abstracts International, Volume: 72-04, Section: B, page: . / Thesis (Ph.D.)--Chinese University of Hong Kong, 2010. / Includes bibliographical references (leaves 59-64). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Electronic reproduction. Ann Arbor, MI : ProQuest Information and Learning Company, [200-] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Electronic reproduction. Ann Arbor, MI : ProQuest Information and Learning Company, [200-] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Abstract also in Chinese.

Traditional multiple hypothesis testing procedures, such as that of Benjamini and Hochberg, fix an error rate and determine the corresponding rejection region. In 2002 Storey proposed a fixed rejection region procedure and showed numerically that it can gain more power than the fixed error rate procedure of Benjamini and Hochberg while controlling the same false discovery rate (FDR). In this thesis it is proved that when the number of alternatives is small compared to the total number of hypotheses, Storeys method can be less powerful than that of Benjamini and Hochberg. Moreover, the two procedures are compared by setting them to produce the same FDR. The difference in power between Storeys procedure and that of Benjamini and Hochberg is near zero when the distance between the null and alternative distributions is large, but Benjamini and Hochbergs procedure becomes more powerful as the distance decreases. It is shown that modifying the Benjamini and Hochberg procedure to incorporate an estimate of the proportion of true null hypotheses as proposed by Black gives a procedure with superior power.<p> Multiple hypothesis testing can also be applied to regression diagnostics. In this thesis, a Bayesian method is proposed to test multiple hypotheses, of which the i-th null and alternative hypotheses are that the i-th observation is not an outlier versus it is, for i=1,...,m. In the proposed Bayesian model, it is assumed that outliers have a mean shift, where the proportion of outliers and the mean shift respectively follow a Beta prior distribution and a normal prior distribution. It is proved in the thesis that for the proposed model, when there exists more than one outlier, the marginal distributions of the deletion residual of the i-th observation under both null and alternative hypotheses are doubly noncentral t distributions. The outlyingness of the i-th observation is measured by the marginal posterior probability that the i-th observation is an outlier given its deletion residual. An importance sampling method is proposed to calculate this probability. This method requires the computation of the density of the doubly noncentral F distribution and this is approximated using Patnaiks approximation. An algorithm is proposed in this thesis to examine the accuracy of Patnaiks approximation. The comparison of this algorithms output with Patnaiks approximation shows that the latter can save massive computation time without losing much accuracy.<p> The proposed Bayesian multiple outlier identification procedure is applied to some simulated data sets. Various simulation and prior parameters are used to study the sensitivity of the posteriors to the priors. The area under the ROC curves (AUC) is calculated for each combination of parameters. A factorial design analysis on AUC is carried out by choosing various simulation and prior parameters as factors. The resulting AUC values are high for various selected parameters, indicating that the proposed method can identify the majority of outliers within tolerable errors. The results of the factorial design show that the priors do not have much effect on the marginal posterior probability as long as the sample size is not too small.<p> In this thesis, the proposed Bayesian procedure is also applied to a real data set obtained by Kanduc et al. in 2008. The proteomes of thirty viruses examined by Kanduc et al. are found to share a high number of pentapeptide overlaps to the human proteome. In a linear regression analysis of the level of viral overlaps to the human proteome and the length of viral proteome, it is reported by Kanduc et al. that among the thirty viruses, human T-lymphotropic virus 1, Rubella virus, and hepatitis C virus, present relatively higher levels of overlaps with the human proteome than the predicted level of overlaps. The results obtained using the proposed procedure indicate that the four viruses with extremely large sizes (Human herpesvirus 4, Human herpesvirus 6, Variola virus, and Human herpesvirus 5) are more likely to be the outliers than the three reported viruses. The results with thefour extreme viruses deleted confirm the claim of Kanduc et al.

Les selenoproteïnes constitueixen una família diversa de proteïnes, caracteritzada per la presència del Seleni (Se), en forma de l'amino àcid atípic, la selenocisteïna (Sec). La selenocisteïna, coneguda com l'amino àcid 21, és similar a la cisteïna (Cys) amb un àtom de seleni en lloc de sofre (S). Les selenoproteïnes són els responsables majoritaris dels efectes biològics del seleni i s'ha observat que poden estar implicades en la infertilitat masculina, el càncer, algunes malalties coronàries,l'activació de virus latents i l'envelliment. La selenocisteïna es codifica pel codó UGA, normalment codó de parada (STOP). Per a la recodificació correcta del UGA són necessaris diversos factors. A la part 3' de la regió no traduïda (UTR) dels transcrits dels gens de selenoproteïnes en organismes eucariotes s'hi troba una estructura de "stem-loop" anomenada SECIS. La proteïna SBP2 interactua amb el SECIS, així com amb el ribosoma, i forma un complex amb el factor d'elongació EFsec i el tRNA de la selenocisteïna, el tRNASec. Donat que el codó TGA normalment significa fi de la traducció, les formes tradicionals de cerca de gens no el reconeixen com a codó codificant. Per aquesta raó ha estat necessari desenvolupar una metodologia específica per a la predicció de gens de selenoproteïnes. En els últims anys, hem contribuït a la descripció del selenoproteoma eucariota amb el descobriment de noves famílies (Castellano et al., 2005), amb l'elaboració de nous mètodes (Taskov et al., 2005; Chapple et al., 2009) i l'anotació de diferents genomes (Jaillon et al., 2004; Drosophila 12 genomes Consortium, 2007; Bovine Genome Sequencing and Analysis Consortium, 2009). Finalment, hem identificat el primer animal que no té selenoproteïnes (Drosophila 12 genomes Consortium, 2007; Chapple and Guigó, 2008), un descobriment soprenent donat que, fins el moment, es creia que les selenoproteïnes eren essencials per la vida animal. / Selenoproteins are a diverse family of proteins containing the trace element Selenium (Se)in the form of the non-canonical amino acid selenocysteine (Sec). Selenocysteine, the 21st amino acid, is similar to cysteine (Cys)but with Se replacing Sulphur. In many cases the homologous gene of a known selenoprotein is present with cysteine in the place of Sec in a different genome. Selenoproteins are believed to be the effectors of the biological functions of Selenium and have been implicated in male infertility, cancer and heart diseases, viral expression and ageing. Selenocysteine is coded by the opal STOP codon (TGA). A number of factors combine to achieve the co-translational recoding of TGA to Sec. The 3' Untranslated regions (UTRs) of eukaryotic selenoprotein transcripts contain a stem-loop structure called a Sec Insertion Sequence (SECIS) element. This is recognised by the Secis Binding Protein 2 (SBP2), which binds to both the SECIS element and the ribosome. SBP2, in turn, recruits the Sec-specific Elongation Factor EFsec, and the selenocysteine transfer RNA, tRNASec. The dual meaning of the TGA codon means that selenoprotein genes are often mispredicted by the standard annotation pipelines. The correct prediction of these genes, therefore, requires the development of specific methods. In the past few years we have contributed significally to the description of the eukaryotic selenoproteome2 with the discovery of novel families (Castellano et al., 2005), the elaboration of novel methods (Taskov et al., 2005; Chapple et al., 2009) and the annotation of different genomes (Jaillon et al., 2004; Drosophila 12 genomes Consortium, 2007; Bovine Genome Sequencing and Analysis Consortium, 2009). Finally, and perhaps most importantly, we have identified the first animal to lack selenoprotein genes (Drosophila 12 genomes Consortium, 2007; Chapple and Guigó, 2008). This last finding is particularly surprising because it had previously been believed that selenoproteins were essential for animal life.

Traditional multiple hypothesis testing procedures, such as that of Benjamini and Hochberg, fix an error rate and determine the corresponding rejection region. In 2002 Storey proposed a fixed rejection region procedure and showed numerically that it can gain more power than the fixed error rate procedure of Benjamini and Hochberg while controlling the same false discovery rate (FDR). In this thesis it is proved that when the number of alternatives is small compared to the total number of hypotheses, Storeys method can be less powerful than that of Benjamini and Hochberg. Moreover, the two procedures are compared by setting them to produce the same FDR. The difference in power between Storeys procedure and that of Benjamini and Hochberg is near zero when the distance between the null and alternative distributions is large, but Benjamini and Hochbergs procedure becomes more powerful as the distance decreases. It is shown that modifying the Benjamini and Hochberg procedure to incorporate an estimate of the proportion of true null hypotheses as proposed by Black gives a procedure with superior power.<p> Multiple hypothesis testing can also be applied to regression diagnostics. In this thesis, a Bayesian method is proposed to test multiple hypotheses, of which the i-th null and alternative hypotheses are that the i-th observation is not an outlier versus it is, for i=1,...,m. In the proposed Bayesian model, it is assumed that outliers have a mean shift, where the proportion of outliers and the mean shift respectively follow a Beta prior distribution and a normal prior distribution. It is proved in the thesis that for the proposed model, when there exists more than one outlier, the marginal distributions of the deletion residual of the i-th observation under both null and alternative hypotheses are doubly noncentral t distributions. The outlyingness of the i-th observation is measured by the marginal posterior probability that the i-th observation is an outlier given its deletion residual. An importance sampling method is proposed to calculate this probability. This method requires the computation of the density of the doubly noncentral F distribution and this is approximated using Patnaiks approximation. An algorithm is proposed in this thesis to examine the accuracy of Patnaiks approximation. The comparison of this algorithms output with Patnaiks approximation shows that the latter can save massive computation time without losing much accuracy.<p> The proposed Bayesian multiple outlier identification procedure is applied to some simulated data sets. Various simulation and prior parameters are used to study the sensitivity of the posteriors to the priors. The area under the ROC curves (AUC) is calculated for each combination of parameters. A factorial design analysis on AUC is carried out by choosing various simulation and prior parameters as factors. The resulting AUC values are high for various selected parameters, indicating that the proposed method can identify the majority of outliers within tolerable errors. The results of the factorial design show that the priors do not have much effect on the marginal posterior probability as long as the sample size is not too small.<p> In this thesis, the proposed Bayesian procedure is also applied to a real data set obtained by Kanduc et al. in 2008. The proteomes of thirty viruses examined by Kanduc et al. are found to share a high number of pentapeptide overlaps to the human proteome. In a linear regression analysis of the level of viral overlaps to the human proteome and the length of viral proteome, it is reported by Kanduc et al. that among the thirty viruses, human T-lymphotropic virus 1, Rubella virus, and hepatitis C virus, present relatively higher levels of overlaps with the human proteome than the predicted level of overlaps. The results obtained using the proposed procedure indicate that the four viruses with extremely large sizes (Human herpesvirus 4, Human herpesvirus 6, Variola virus, and Human herpesvirus 5) are more likely to be the outliers than the three reported viruses. The results with thefour extreme viruses deleted confirm the claim of Kanduc et al.